U.S. patent number 5,247,460 [Application Number 07/536,402] was granted by the patent office on 1993-09-21 for apparatus and method for improving quality of comminuted meat products.
Invention is credited to Robert A. LaBudde.
United States Patent |
5,247,460 |
LaBudde |
September 21, 1993 |
Apparatus and method for improving quality of comminuted meat
products
Abstract
An apparatus and method for estimating and evaluating
acceptability of process variations in a blended meat processing
facility. The apparatus implementing the method includes a
keyboard, a data storage device, a program storage device, a
calculating system and a display device. Information relating to
moisture, fat, protein and Added Water are provided to the data
storage by an keyboard operator. The calculator in accordance with
present functions computes various factors relating to the input
data and conducts tests upon the statistical validity of such
computations. Providing statistical validity has been maintained,
the display device then displays the outputs indicative of the
variability of moisture in the blend and in one embodiment is used
to control inputs and/or processing steps in the blended meat
product to meet preset regulatory requirements.
Inventors: |
LaBudde; Robert A. (Virginia
Beach, VA) |
Family
ID: |
24138345 |
Appl.
No.: |
07/536,402 |
Filed: |
June 12, 1990 |
Current U.S.
Class: |
702/81;
426/231 |
Current CPC
Class: |
A23L
13/60 (20160801); G01N 33/12 (20130101) |
Current International
Class: |
A23L
1/317 (20060101); G01N 33/02 (20060101); G01N
33/12 (20060101); G06F 015/46 () |
Field of
Search: |
;364/550,551.01,552,554,575,496,502 ;426/231,246,641 |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
Kramlich et al. Processed Meats, The AVI Publishing Co., Inc. pp.
158-181 and 230-311; 1973..
|
Primary Examiner: Black; Thomas G.
Assistant Examiner: Zanelli; Michael
Attorney, Agent or Firm: Arant; Gene W.
Claims
What is claimed is:
1. Apparatus for monitoring undesired variations in the blend
ratio, the cooking process, and the laboratory testing and analysis
process, in the manufacture of a comminuted meat product in
successive batches by selecting a plurality of meat components each
of which has its own characteristics of protein, fat, and moisture
content, blending the components in a selected blend ratio to
produce an emulsion, cooking the emulsion and thereby changing its
moisture content to provide a cooked product, and then by a
laboratory process testing and analyzing the cooked product to
measure its conformance to a predetermined minimum protein content,
to a predetermined maximum fat content, and to a predetermined
maximum moisture content; said apparatus comprising, in
combination:
(a) computer means including a microprocessor having data storage
means including a random access memory, keyboard means for entering
data into said data storage means, and an EPROM associated with
said microprocessor for storing a program for said
microprocessor;
(b) said keyboard means being adapted for entering into said data
storage means an average value for each of moisture, protein, fat
content, and added water of the cooked product, and also a standard
deviation for each of such average values;
(c) said keyboard means being also adapted for entering into said
data storage means an estimated average value of shrinkage of the
cooked product;
(d) said keyboard means further being adapted for entering into
said data storage means estimated standard deviations of the three
variables (1) moisture content of the uncooked emulsion, (2)
shrinkage of the cooked product, and (3) laboratory error in
measurement of the protein content of the cooked product;
(e) computer program means controlled by said EPROM and responsive
to said stored average values, standard deviations thereof, and two
of said estimated standard deviations of said three variables, for
calculating a standard deviation of the third one of said three
variables; and
(f) computer program means for comparing said calculated standard
deviation with a respectively associated process control standard
to provide a comparison result.
Description
BACKGROUND AND SUMMARY OF THE INVENTION
At least a portion of the disclosure of this patent document
contains material which is subject to copyright protection. The
copyright owner has no objection to the facsimile reproduction by
anyone of the patent document or the patent disclosure, as it
appears in the Patent and Trademark Office patent file or records,
but otherwise reserves all copyright rights whatsoever.
1. Field of the Invention
The present invention is generally related to the meat processing
industry and is specifically related to an apparatus and method for
determining the source of and controlling variations in comminuted
meat products.
2. Discussion of the Prior Art
The meat processing industry is regulated by the U.S. Department of
Agriculture (USDA) on the basis of the chemical analysis of
finished products which are marketed to the consumer. Sample lots
of products are drawn on a periodic basis by USDA inspectors for
chemical analysis to verify compliance with the quality control
regulations. Usually, such sampling will actually be done by the
meat processing company laboratory after having been certified for
accuracy by the USDA.
If a meat product analysis indicates a lack of compliance to the
standards, the inspector will denote the entire lot of the meat
products as being "retained" which means not only that that "lot"
must be reworked and cannot be shipped, but that there will be a
tightened inspection in the future. Because of the cost associated
with a "retained" lot, meat processors are careful to target their
final product content so that violations of the USDA requirements
are relatively small.
Meat processing is subject to numerous sources of variation, not
found in other industries, making the problem of product
consistency quite difficult. Raw meat trimmings are sold to meat
processors based upon the fat content and incoming lots are
routinely analyzed by the meat processor to check for the
supplier's contractual compliance. Variations of fat content within
.+-.2% of standard are considered acceptable, although this
criteria is normally applied on the high fat side. The USDA also
regulates "USDA Added Water" which is defined by the USDA as
"moisture -4.times.protein." Regulation of processed meat products
such as sausage, e.g., franks, bologna, luncheon meats, etc., is
based upon maximum limits on the fat and "USDA Added Water" content
of the consumer product.
Raw meat materials are typically blended together in a partial
batch called a "preblend" or an "uncorrected" blend, which is then
sampled and chemically analyzed. Based upon the analysis, the
remaining material is added in adjusted amounts to "correct" the
preblend to the target specification which may be a slightly
conservative version of the USDA regulations governing the
particular meat products. The adjusted "final" or "corrected" blend
is then comminuted and passed to the stuffing department, where it
is injected into casings. The product is then cooked, cooled,
casings removed and packaged for shipping.
Meat processors normally conduct their own quality assurance
testing to provide advance notice of possible regulatory
noncompliance. Such testing normally involves chemical analysis of
sampled lots for moisture, fat, protein and USDA Added Water (USDA
AW). The principal sources in variation in finished product
analyses result from three sources at the meat processing company.
First, there is a variation in composition of the final blend or
"emulsion" related to the actual blending step. Other variations in
"emulsion" analysis may result from improper material use or
weights, errors in assumed raw meat analysis, laboratory errors in
the preblend analysis, if performed, etc.
Secondly, there are variations due to moisture loss during the
cooking and holding times (this moisture loss is commonly called
"shrinkage"). Additional "shrinkage" variations occur in moisture
shrink loss resulting from improper smokehouse loading or
schedules, faulty smokehouse equipment, abnormal holding times,
etc. Thirdly, a variation is introduced in the imprecision of the
laboratory analysis for moisture, fat and protein.
The laboratory analysis error can be particularly critical since
protein analysis is weighted by a factor of 4 in the definition of
the USDA AW. Minor variations in the protein analysis can result
from insufficient mixing or comminution of the laboratory sample,
the very small test weights utilized (typically 2 grams for the
protein test) and variations between personnel, improper times of
digestion, extraction or distillation.
Because of the large number of sources of variations encountered in
meat processing, it is difficult to identify and remove assignable
causes of product variation. As a result, processors must reduce
their fat and USDA AW targets to provide a statistical margin of
error to avoid any significant retainage. This conservative
estimate of fat and USDA AW target specifications results in a
"giveaway" in product analysis resulting in a 1-5% increased
product cost. Therefore, it can be seen that the ability to provide
product closer to a 1% cost rather than a 5% cost results in a
significant cost savings and increased profit to the meat
processor.
It is therefore extremely desirable in the meat processing industry
to have reasonable estimates on the sizes of these three principal
sources of variation in finished product analysis so that active
correction action may be taken to reduce and control them.
Obviously, a reduction in product chemical variability immediately
results in a reduced cost of production by reducing the amount of
the "giveaway." An estimation of the sizes of the three principal
sources of product variation allows quick troubleshooting of
problems so as to correct the area of production, i.e., blending,
postblending or laboratory.
In the past, estimation of the blending variation could only be
done by actual sampling and chemical analysis of samples of the
final blend of meat, preferably after final comminution before
stuffing into casings. The between-lots standard deviations of
moisture and fat for the same product target specifications measure
and provide an indication of the "uncorrected" blend variation.
However, obtaining this extra sampling and analysis results in
significant additional costs being incurred for this process
monitoring.
In the past there has been no accepted method for determination of
overall product moisture loss ("shrinkage") from the stuffing phase
to the final packaging phase. The common practice has been to
measure and monitor the principal component of shrink loss, that
due to cooking, by weighing racked products in and out of the
smokehouse. These measurements have many sources of error which
limit their use for process control and include: difficulty and
expense of taring (the initial zero weighing process of the racks)
and identifying the racks accurately; inadvertent movement of the
product from tared racks to others; loss of spray coatings of smoke
treatments (which result in apparent shrinkage); lack of care by
plant personnel in weighing in a busy production environment, etc.
Also significant is a lack of measurement of the pre-cook and
post-cook shrinkages, which can amount to several percent and can
vary from batch-to-batch due to differences in holding times,
etc.
Errors in the finished product laboratory analyses are difficult to
detect and measure. Because of the unique lot analyses, the
perishable and changeable nature of the products, small lab sample
sizes, etc., it is difficult to reproduce the exact condition of a
test in two different laboratories. Although laboratories may be
"certified" by comparative studies with the USDA and standard
methods of analysis are used, it is notorious in the industry that
values obtained by the USDA laboratories, or even by outside
testing laboratories, cannot in general be trusted as a definitive
measure of the "true" analysis.
As a consequence, meat processing companies generally have no good
idea of the exact precision and accuracy of its own laboratory.
Some companies will validate their results by a between-methods
comparison of moisture or fat values obtained by two different
instruments or techniques. However, the effectiveness of such tests
varies with the type of sample and product and generally the
process of determining precision of this method is too burdensome
to carry out for each and every product. It should be noted that
the protein measurement analysis is particularly critical and there
is currently only one accepted standard method for protein
analysis. Therefore, with this measurement a "between-methods"
measurement of precision cannot be attempted.
SUMMARY OF THE INVENTION
Because all meat processors perform daily analyses of their
products for moisture, fat, protein and USDA AW (or some subset of
these), large numbers of such analyses are accumulated over time
but are used only for negative results (i.e., general indication of
variable products). The present invention is to utilize the
outgoing product analyses to diagnose the sources and sizes of
product variation in order to permit isolation of causes of such
variation so they may be removed, reduced or otherwise
controlled.
It is therefore an object of the present invention to provide a
method and apparatus for estimating and evaluating the
acceptability of lot-to-lot process variations for a blended meat
product made to a constant target or specification and providing a
correction control to the processing input steps.
According to the present invention a set of good assumptions are
made which render it unnecessary to obtain direct measurements of
either the moisture content of the emulsion or the shrink. Standard
deviations of two unknowns are estimated on the basis of historical
experience. It is then possible to directly calculate a third
unknown, which is a standard deviation that is critical to the
accuracy of the overall process.
More specifically, there are three such standard deviations which
are critical: moisture content of the blend; shrink that occurs
during cooking; and laboratory error in measurement of protein
content of the cooked product. The present invention makes it
possible to obtain a fairly precise calculation of each of these
three unknowns by first making reasonable assumptions as to the
values of the other two.
In a preferred embodiment of applicant's invention, data from which
it is possible to determine blend variation, moisture-loss
variation and/or protein analysis variation of the blended meat
product is inputted through a keyboard and stored in a data
storage. These process variations in the meat product are
calculated based upon the data stored in said data storage and
displayed by an appropriate display means. Advantageously,
applicant's invention may be conveniently implemented in a
preprogrammed hand-held calculator and the method may be
advantageously implemented by utilizing the calculated process
variation information in a feedback loop to automatically control
the variables in the desired meat processing steps.
BRIEF DESCRIPTION OF THE DRAWINGS
Various embodiments of applicant's invention may be better
understood by reference to the following drawings wherein:
FIG. 1 comprises a block diagram of an apparatus according to
applicant's invention;
FIG. 2a through 2g are a flowchart of the steps taken in accordance
with one embodiment of the present invention; and
FIG. 3 is a flowchart diagram of applicant's inventive method as
applied to an automated meat processing system.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
Referring now to FIG. 1, there is shown an overall block diagram of
a simple embodiment of the applicant's invention. A keyboard 10 is
utilized to input parameters, as measured values or estimates,
which comprise information relating to blend variation,
moisture-loss variation and protein analysis variation of the meat
products being considered. This information is supplied to a data
storage means 12 which stores the information in a Random Access
Memory (RAM).
Calculator 14 is suitably programmed, for example by program
storage 18, so as to access the memory of data storage 12 and
process the information in an appropriate fashion so as to provide
the desired process variations of the meat products which can be
supplied as a control output to effect improvements in an automated
meat processing system and/or provided to a display 16 in order to
permit an operator to review the output and then make the desired
processing step corrections.
In a preferred embodiment, the present invention is implemented
with a Sharp brand hand-held PC 1350/1360 pocket computer which
includes an electronically-programmable read-only memory (EPROM).
The EPROM is loaded prior to operation with a suitable program, a
source listing of which is attached as Appendix A hereto. In order
to facilitate understanding of the operations performed and the
implementation of the program, a detailed discussion of the
processing steps will follow. However, to simplify this discussion,
a glossary of terms is provided which includes symbols used in the
specification and claims, and a cross-reference with symbols used
in the program source listing and ad well as a definition of those
symbols.
______________________________________ GLOSSARY OF SYMBOLS Spec/
Claims Program Meaning ______________________________________ M
AV(MX) Average value of moisture for lot-to-lot samples F AV(FX)
Average value of fat for lot-to-lot samples P AV(PX) Average value
of meat protein for lot-to-lot samples AW AV(AX) Average value of
Added Water for lot-to-lot samples s.sub.M S(MX) Standard deviation
of moisture for lot-to-lot samples s.sub.F S(FX) Standard deviation
of fat for lot-to-lot samples s.sub.P S(PX) Standard deviation of
protein for lot-to-lot samples s.sub.AW S(AX) Standard deviation of
added water for lot-to-lot samples s.sub.m SM Estimated standard
deviation of moisture analysis error s.sub.f SF Estimated standard
deviation of fat analysis error s.sub.p SP Estimated (and later
recalculated) standard deviation of protein analysis error s S
Average processing moisture shrink loss s.sub.s .sqroot.VS Standard
deviation of shrink s.sub.B MM Beginning estimate of standard
deviation of moisture in final blend V1 V1 Estimate of
s.sub.b.sup.2 from fat V2 V2 Estimate of s.sub.b.sup.2 from
moisture s.sub.b .sqroot.VM Calculated estimate of standard
deviation of moisture in corrected blend: Note, that s.sub.B and
s.sub.b are both estimates of the same end quantity. s.sub.aw
.sqroot.X Calculated estimate of standard deviation of Added Water
determination error ______________________________________
The following is a brief discussion of steps carried out to
implement one embodiment of the inventive method and apparatus with
reference to the flowchart disclosed in FIGS. 2a through 2g.
1. Obtain estimates of, or calculate from measurements, average
moisture M, average fat F, average protein P and average Added
Water AW and of standard deviations s.sub.M, s.sub.F, s.sub.P and
s.sub.AW, respectively. These can be inputted directly by means of
the keyboard means or other data input device, or as computed from
measured characteristics of outgoing product after shrinkage.
Obtain estimates of the standard deviations of the between sample
laboratory error in moisture s.sub.m, fat s.sub.f, and protein
s.sub.p. If the standard deviations of s.sub.m, s.sub.f, s.sub.p
are not known (which is usually the case), the program initially
uses 0.3%, 0.4% and 0.2%, respectively, which have been determined
as typical in such systems. If the final blend is a "corrected"
blend, s.sub.B is set to 0.4% and if an "uncorrected" blend,
s.sub.B is set to 1.0%.
2. An estimate of the average processing moisture shrink loss (s)
from uncooked emulsion to the time of lab analysis is also
inputted. This number is typically 3-15% for typical cooked sausage
products and can be more or less for other products.
3. The terms s.sub.aw.sup.2 and Y are calculated in accordance with
Equations 1 and 2 as follows, where the term represented by
s.sub.aw.sup.2 is the laboratory Added Water variance and Y is a
function of the measured Added Water variance (related to the
standard deviation of Added Water for the samples):
The calculations of the two terms are compared and if
s.sub.aw.sup.2 is greater than or equal to Y, then the lab error is
too large and the term "Lab Error Too Large" is displayed.
4. Shrink variance is computed based upon the following:
##EQU1##
In equations 3 and 4, the x indicates a multiplication function and
the standard deviation of moisture in blend s.sub.B is assumed to
be 0.4% if "correction is used and 1.0% if not. The term 0.1 is an
estimate (viz. 1.0-4.times.0.275) of the contribution of the meat
composition variation to Added Water variation, and the term 0.275
is an estimate of the ratio of standard deviation of protein to
that of moisture due to raw meat composition variations. The factor
of 0.275 is a compromise which represents with reasonable accuracy
the bulk of processed meats produced in North America. The factor
varies from 0.2 for comminuted chicken or turkey meat to 0.3 for
chicken or turkey or beef or pork muscle meat.
Since the meat processor is aware of the species composition of his
products, under ideal circumstances he could compute the weighted
average by composition of the individual species' factors and use
this value to replace the value 0.275 as well as 1.0-4.times.value
to replace 0.1 in equation 3 as follows:
where the numerical coefficients are determined by correlation
analysis of measured chemical content of the meat, and the %
compositions are of meat protein (ideally) or simply of meat in the
blend. Generally the difference from the value 0.275 will not be
significant except possibly in the case that all of the meat is
from comminuted poultry.
5. Determine whether the results are reasonable. If s.sub.s.sup.2
is less than zero, then the phrase "Results Not Sensible" is
reported and the analysis terminates by returning to the beginning
of the process. Otherwise, s.sub.s is reported and stored as the
computed standard deviation of shrink.
6. s.sub.s is compared to 1% and if greater than 1% the display
indicates "Exceeds 1%." This warning indicates that the cooking
steps are too variable for good process control. If the standard
deviation of shrink is less than 0.5%, the phrase "Too Small (less
than 0.5%)" is displayed, indicating an abnormally low, and
possibly incorrect, estimate of shrink variation was found.
7. Lab protein is calculated in accordance with the following
equation:
If s.sub.p.sup.2 is less than zero, then "Protein Error Too Small"
is reported since it apparently cannot be computed accurately. If
s.sub.p is greater than 0.32%, then the term "exceeds 0.3%" is
reported which indicates excessive lab protein analysis error
although the system continues.
8. The standard deviation of moisture in the blend (s.sub.b) is
computed at this point in two different manners. First, if fat
statistics were not provided, the system indicates V1 (estimate of
s.sub.b.sup.2 from fat) is set to zero and the standard deviation
computation based upon fat information is avoided. If fat
statistics were provided, then the term V1 is calculated by
equation 5 as follows and stored.
In equation 5, the term 1.285 is an estimate of the ratio of the
standard deviation fat to that of moisture due to raw meat
composition variations. The factor of 1.285 is a compromise which
represents with reasonable accuracy the bulk of processed meats
produced in North America. The factor varies from 1.2 for
comminuted chicken or turkey meat to 1.3 for chicken or turkey or
beef or pork muscle meat. Since the meat processor is aware of the
species composition of his products, under ideal circumstances he
could compute the weighted average by composition of the individual
species' factors and use this value to replace the value 1.285 in
equation 5, as follows:
where the numerical coefficients are determined by correlation
analysis of measured chemical content of the meat, and the %
compositions are of meat fat (ideally) or simply of meat in the
blend. Generally the difference from the value 1.285 will not be
significant except possibly in the case that all of the meat is
from mutton or comminuted poultry.
9. If moisture statistics were not provided, the system sets V2
equal to zero and bypasses the estimate of standard deviation of
moisture in the blend calculation based on moisture statistics. If
moisture statistics are given, then the term V2 (estimate of
s.sub.b.sup.2 from moisture) is calculated in accordance with
equation 6 as follows:
10. The average of the two estimates s.sub.b.sup.2 is computed in
accordance with s.sub.b.sup.2 =0.5 (V1+V2). If moisture statistics
were not provided, then s.sub.b.sup.2 is set to be equal to V1. If
fat statistics were not given, then s.sub.b.sup.2 is set to V2. A
further comparison is made to determine whether V1 is less than
0.05 and V2 is greater than V1. If so, then s.sub.b.sup.2 is set
equal to V2. If not, V2 is tested to determine whether it is less
than 0.05 and V2 is less than V1. If so, s.sub.b.sup.2 is set equal
to V1. In any case, s.sub.b.sup.2 is then tested to be less than or
equal to zero. If it is, the display system indicates "Can't Find
Emulsion Variance" and the program terminates.
If s.sub.b.sup.2 is greater than zero, the standard deviation of
moisture in blend (s.sub.b) is displayed. If s.sub.b.sup.2 is less
than 0.05, the display indicates "Too Small (less than 0.2%)",
indicating an abnormally low and possibly incorrect estimate. If
s.sub.b.sup.2 is greater than or equal to 0.25 (or 1.5 if no
correction is used) the display indicates "Exceeds 0.5%" (or
"Exceeds 1.2%" if no correction is used) and, if not, the program
continues. As a "preblend" may or may not be used, there will or
will not be a correction adjustment in the final blend.
The shrink variation s.sub.s.sup.2 is then tested to be greater
than 1%. If it is, then display "Shrink Problem".
If a correction is used and s.sub.b.sup.2 is greater than 0.25 or
if no correction was used and s.sub.b.sup.2 is greater than 1.5,
the display will indicate "Emulsion Problem". If neither of these
conditions is met, the program terminates.
It is noted that although Added Water as defined by the USDA is
moisture minus 4.times.protein, a different definition (i.e.,
coefficient of the multiplier for protein) of from 3.3 to 4.0 would
give usable results (this would provide a coefficient of from -0.1
to +0.1 in the formula for s.sub.s). The ideal definition of Added
Water would be in the range of 3.5 to 3.7 (nominal 3.6) which would
cause the coefficient of s.sub.B in s.sub.s to change from 0.1 to
near zero, totally decoupling the two sources of variation in the
equation. However, the factor of 0.1 is so small, it effectively
performs the same function (less than 1% contribution).
It should also be noted that the standard deviation of fat in the
meat product after blending but before shrinkage might also have to
be calculated as 1.285 s.sub.b. However, s.sub.b directly is
usually a preferable process control variable.
It can be seen from the above that while the standard deviation of
moisture loss from shrinkage (s.sub.s) is calculated and is then
used in the derivation of V1 and V2, if this is known it can be
directly inputted bypassing Equation 3 and eliminating the
necessity for some of the inputs required for the s.sub.s
calculation. This is true for both equations V1 and V2.
Furthermore, although in a preferred embodiment of applicant's
invention both V1 and V2 are calculated (if both fat and moisture
are known) the invention would still be operable if only a single
equation 5 or 6 is adopted, i.e., V1 or V2. In the same manner,
s.sub.B could be measured and directly inputted.
Applicant's processing method can best be implemented by including
a feedback loop to permit adjustment of input parameters in a meat
processing system so as to automatically control meat products to a
target standard. A flowchart of such a control system is
illustrated in FIG. 3. While the previous description of the
flowchart shown in FIGS. 2a through 2g are applicable as well, it
is noted that after the three sources of variation are isolated,
the input quantities are adjusted to meet the desired output
standards.
It will be seen that based upon the above description and the
accompanying figures, that many modifications and variations of
applicant's invention will be possible. Depending upon the specific
meat products used different factors and estimations will be
obvious to those of ordinary skill in the art in view of this
disclosure. While the invention has been described in connection
with what is presently considered to be the most practical and
preferred embodiment, it is to be understood that the invention is
not to be limited to the disclosed embodiment, but on the contrary,
is intended to cover various modifications and equivalent
arrangements included within the spirit and scope of the appended
claims.
__________________________________________________________________________
APPENDIX A
__________________________________________________________________________
13000 "PROD": REM PRODUCT DIAGNOSIS 03.12.90 08.00 13010 CLEAR: DIM
L$(6),X(6,20),LL$(6),AV(6),S(6),MN(6),MX(6) 13020 RESTORE 13040
13030 FOR I=1 TO 6: READ LL$(I): NEXT I 13040 DATA
"MOISTURE","FAT","PROTEIN","OTHER","USDA AW","M+F+P" 13050 CLS:
WAIT 0 13060 PRINT "PRODUCT DIAGNOSIS" 13070 PRINT "Which
Attributes?" 13080 PRINT "M=MOIST F=FAT P=PROT" 13090 PRINT
"O=OTHER A=USDA AW": WAIT 13100 INPUT "Letters in order: ";L$ 13110
AX=0: MX=0: PX=0: FX=0: C$="Y" 13120 FOR I=1 TO LEN(L$) 13130 IF
MID$(L$,I,1)="M" LET MX=I: L$(MX)=LL$(1) 13140 IF MID$(L$,I,1)="F"
LET FX=I: L$(FX)=LL$(2) 13150 IF MID$(L$,I,1)="P" LET PX=I:
L$(PX)=LL$(3) 13160 IF MID$(L$,I,1)="A" LET L$(I)=LL$(5): AX=I
13170 IF MID$(L$,I,1)<>"0" THEN 13200 13180 L$(I)=LL$(4)
13190 INPUT "LABEL FOR OTHER: ";L$(I) 13200 NEXT I 13210 CLS: WAIT
0 13220 PRINT "Stats from Where?" 13230 PRINT "1=RANGES 2=DATA
3=ENTER": WAIT 13240 INPUT "Where from? ";IS 13245 IF MX=0 OR PX=0
OR AX<>0 OR IS<>2 THEN 13260 13250 L$=L$+"a":
AX=LEN(L$): L$(AX)=LL$(5) 13260 IF MX=0 OR PX=0 OR FX=0 OR
IS<>2 THEN 13270 13265 L$=L$+"t": L$(LEN(L$))=LL$(6) 13270 ON
IS GOSUB 34500, 34000, 13500 13280 GOSUB 34700 13290 SM=.3: SF=.4:
SP=.2: SS=1 13300 IF AX=0 THEN 13210 13305 USING "#####.###" 13310
CLS: WAIT 0 13320 PRINT "Product Diagnosis" 13330 PRINT "Estimates
of Lab Errors?": WAIT 13340 INPUT "Moisture: ";SM 13350 INPUT "Fat:
";SF 13360 INPUT "Protein: ";SP 13362 INPUT "Used Correction? ";C$
13364 MM=.4: IF C$<>"Y" THEN LET MM=1.0 13370 INPUT "Ave."
Shrink (0-100): ";S 13375 S=.01*S 13376 X=SM 2+16*SP 2: Z=S(AX) 2
13377 IF X<.7*Z THEN 13380 13378 PRINT "Lab Error Too Large!"
13379 PRINT "Can't Find Shrink Var.!" 13380
VS=(Z-X-(MM*(1-4*.275)/(1-S)) 2)*((1-S)/(1-.01*AV(AX))) 2 13381 IF
VS>0 THEN 13385 13382 PRINT ">> Results not Sensible!"
13383 GOTO 13310 13385 PRINT "Shrink Var.:",SQR(VS) 13386 IF
VS>1 PRINT ">> Exceeds 1%!" 13387 IF VS<.25 PRINT
">> Too small (<0.5%)" 13388 VP=S(PX) 2-(.01*AV(PX)/(1-S))
2*VS-(.275*MM/(1-S)) 2 13389 IF VP>0 THEN 13392 13390 PRINT
">> Protein Error Too Small!" 13391 GOTO 13393 13392 PRINT
"Prot. Error:",SQR(VP) 13393 IF VP>.1 PRINT ">>Exceeds
0.3%!" 13394 VI=0: IF FX=0 THEN 13396 13395 VI=(S(FX)
2-(AV(FX)*.01/(1-S)) 2*VS-SF 2)*((1-S)/1.285) 2 13396 V2=0: IF MX=0
THEN 13400 13399 V2=(S(MX) 2-((1-.01*AV(MX))/(1-S)) 2*VS-SM
2)*(1-S) 2 13400 VM=.5*(V1+V2) 13401 IF MX=0 LET VM=V1 13402 IF
FX=0 LET VM=V2 13405 IF VI<.05 AND V2>V1 LET VM=V2 13407 IF
V2<.05 AND V1>V2 LET VM= V1 13410 IF VM>0 THEN 13425 13415
PRINT ">> Can't Find Emuls. Var.!" 13420 GOTO 13310 13425
PRINT "Emuls. Var.:",SQR(VM) 13430 IF VM<.05 PRINT ">> Too
small (0.2%)!" 13431 IF C$="Y" AND VM>.25 PRINT ">>
Exceeds 0.5%!" 13433 IF C$<>"Y" AND VM>1.5 PRINT ">>
Exceeds 1.2%!" 13440 IF VS>1 PRINT "** SHRINK PROBLEM **" 13450
IF C$="Y" AND VM<=.25 THEN 13460 13455 IF C$<>"Y" AND
VM<1.5 THEN 13460 13457 PRINT "** EMULSION PROBLEM **" 13460
GOTO 13310 13500 REM ENTERED 13510 FOR I=1 TO LEN(L$) 13520 CLS:
WAIT 0 13530 PRINT "Enter Stats for ";L$(I) 13540 INPUT "Average:
";AV(I) 13550 INPUT "Standard Dev.: ";S(I) 13560
MN(I)=AV(I)-1.96*S(I): MX(I)=AV(I)+1.96*S(I) 13570 NEXT I 13580
RETURN
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* * * * *